"""simple docstring"""



import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


SCREAMING_SNAKE_CASE__:List[Any]									=			pytest.mark.integration



@pytest.mark.parametrize("path"   ,    ["paws", "csv"]				)
def 	_lowerCamelCase(	a   ,    a				):
       inspect_dataset(a   ,    a				)
       __a       =    path + ".py"
       assert script_name in os.listdir(a				)
       assert "__pycache__" not in os.listdir(a				)



@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning"				)
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning"				)
@pytest.mark.parametrize("path"   ,    ["accuracy"]				)
def 	_lowerCamelCase(	a   ,    a				):
       inspect_metric(a   ,    a				)
       __a       =    path + ".py"
       assert script_name in os.listdir(a				)
       assert "__pycache__" not in os.listdir(a				)



@pytest.mark.parametrize(
    "path, config_name, expected_splits"   ,    [
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a   ,    a				):
       __a       =    get_dataset_config_info(a   ,    config_name=a				)
       assert info.config_name == config_name
       assert list(info.splits.keys()				) == expected_splits



@pytest.mark.parametrize(
    "path, config_name, expected_exception"   ,    [
        ("paws", None, ValueError),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a   ,    a				):
       with pytest.raises(a				):
              get_dataset_config_info(a   ,    config_name=a				)



@pytest.mark.parametrize(
    "path, expected"   ,    [
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a				):
       __a       =    get_dataset_config_names(a				)
       assert expected in config_names



@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"   ,    [
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a   ,    a				):
       __a       =    get_dataset_infos(a				)
       assert list(infos.keys()				) == expected_configs
       __a       =    expected_configs[0]
       assert expected_config in infos
       __a       =    infos[expected_config]
       assert info.config_name == expected_config
       assert list(info.splits.keys()				) == expected_splits_in_first_config



@pytest.mark.parametrize(
    "path, expected_config, expected_splits"   ,    [
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a   ,    a				):
       __a       =    get_dataset_infos(a				)
       assert expected_config in infos
       __a       =    infos[expected_config]
       assert info.config_name == expected_config
       assert list(info.splits.keys()				) == expected_splits




@pytest.mark.parametrize(
    "path, config_name, expected_exception"   ,    [
        ("paws", None, ValueError),
    ]   ,    )
def 	_lowerCamelCase(	a   ,    a   ,    a				):
       with pytest.raises(a				):
              get_dataset_split_names(a   ,    config_name=a				)

"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__:Optional[Any]									=			{"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ReformerConfig"""]}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:Optional[Any]									=			["""ReformerTokenizer"""]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:List[str]									=			["""ReformerTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE__:int									=			[
       """REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """ReformerAttention""",
       """ReformerForMaskedLM""",
       """ReformerForQuestionAnswering""",
       """ReformerForSequenceClassification""",
       """ReformerLayer""",
       """ReformerModel""",
       """ReformerModelWithLMHead""",
       """ReformerPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_reformer import ReformerTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_reformer_fast import ReformerTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_reformer import (
          REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          ReformerAttention,
          ReformerForMaskedLM,
          ReformerForQuestionAnswering,
          ReformerForSequenceClassification,
          ReformerLayer,
          ReformerModel,
          ReformerModelWithLMHead,
          ReformerPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE__:int									=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
